Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…This research aims to compare the key machine learning approaches, Namely Support Vector Machines (SVM), Random Forest (RF) and Decision Trees (DT), in their ability to classify Intrusion Detection Systems (IDS) via routing networks over distributed computing systems. …”
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Laboratory and numerical investigation of cutting tool performance using a new small-scale linear cutting machine by Hamid Chakeri, Amin Maleki, Hadi Shakeri, Mohammad Darbor, Hamid Mousapour

“…Additionally, all laboratory tests were numerically modeled using the finite element method under identical boundary conditions. …”
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An explainable machine learning framework for railway predictive maintenance using data streams from the metro operator of Portugal by Silvia García-Méndez, Francisco de Arriba-Pérez, Fátima Leal, Bruno Veloso, Benedita Malheiro, Juan Carlos Burguillo-Rial

“…The proposed method implements a processing pipeline comprised of sample pre-processing, incremental classification with Machine Learning models, and outcome explanation. …”
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Design Optimization and Performance Evaluation of an Automated Pelleted Feed Trough for Sheep Feeding Management by Xinyu Gao, Chuanzhong Xuan, Jianxin Zhao, Yanhua Ma, Tao Zhang, Suhui Liu

“…The results indicated that the Matlab method could calibrate the Johnson–Kendall–Roberts (JKR) model’s surface energy. The optimal slope was found to be 63°, with optimal baffle heights of 28 mm for fine and medium pellets and 30 mm for coarse pellets. …”
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SimProx: A Similarity-Based Aggregation in Federated Learning With Client Weight Optimization by Ayoub El-Niss, Ahmad Alzu'Bi, Abdelrahman Abuarqoub, Mohammad Hammoudeh, Ammar Muthanna

“…Federated Learning (FL) enables decentralized training of machine learning models across multiple clients, preserving data privacy by aggregating locally trained models without sharing raw data. …”
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Deep Learning–Based Enhanced Optimization for Automated Rice Plant Disease Detection and Classification by P. Preethi, R. Swathika, S. Kaliraj, R. Premkumar, J. Yogapriya

“…This study introduces an advanced approach for automated rice plant disease detection and classification by integrating deep learning and metaheuristic optimization techniques. Specifically, a deep dense neural network (DNN) is employed for its capacity to capture intricate patterns in images and extreme learning machine (ELM) for classification. …”
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Optimal thresholds and key parameters for predicting influenza A virus transmission events in ferrets by Troy J. Kieran, Xiangjie Sun, Taronna R. Maines, Jessica A. Belser

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Modeling of Exhaust Gas Temperature at the Turbine Outlet Using Neural Networks and a Physical Expansion Model by Alessandro Brusa, Alice Grossi, Mirco Lenzi, Fenil Panalal Shethia, Nicolò Cavina, Ioannis Kitsopanidis

“…The model utilizes the exhaust gas temperature upstream of the turbine, a model for which was developed in a previous work of the authors. …”
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AI-driven health analysis for emerging respiratory diseases: A case study of Yemen patients using COVID-19 data by Saleh I. Alzahrani, Wael M. S. Yafooz, Ibrahim A. Aljamaan, Ali Alwaleedi, Mohammed Al-Hariri, Gameel Saleh

“…The ARMA model demonstrated promising performance. Additionally, eight machine learning (ML) classifiers and deep learning (DL) models were utilized to identify COVID-19 severity indicators. …”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…The technique utilizes Machine Learning (ML), particularly leveraging the Regression Tree (RT) model. …”
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Deep learning assisted non-invasive lymph node burden evaluation and CDK4/6i administration in luminal breast cancer by Yuhan Liu, Jinlin Ye, Zecheng He, Mingyue Wang, Changjun Wang, Jie Lang, Yidong Zhou, Wei Zhang

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Adapting physics-informed neural networks to improve ODE optimization in mosquito population dynamics. by Dinh Viet Cuong, Branislava Lalić, Mina Petrić, Nguyen Thanh Binh, Mark Roantree

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A Cost of Misclassification Adjustment Approach for Estimating Optimal Cut-Off Point for Classification by O.-A. Ampomah, R. Minkah, G. Kallah-Dagadu, E. N. N. Nortey

“…Classification is one of the main areas of machine learning, where the target variable is usually categorical with at least two levels. …”
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Predictive Maintenance of HVAC Systems using Deep Learning for Optimized Building Energy Efficiency by Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mostafa Khanzadi

“…Techniques in Artificial Intelligence (AI), such as Machine Learning (ML) and Deep Learning (DL), are now used to optimize HVAC energy efficiency as well as facilitate predictive maintenance, which reduces downtime as well as costs. …”
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Advancements in Optimization Techniques for Active Magnetic Bearing Systems: Current Trends and Future Directions by Tasnemul Hasan Nehal, Waleed M. Hamanah, Mohammad Ali Abido

“…The emergence of hybrid optimization, adaptive fuzzy controllers, and machine learning-enhanced models is pushing the boundaries of AMB performance, offering substantial gains in stability, efficiency, fault tolerance, and vibration suppression. …”
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A novel approach based on XGBoost classifier and Bayesian optimization for credit card fraud detection by Mohammed Tayebi, Said El Kafhali

“…Our proposed solution outperforms other machine learning models, as demonstrated by these experimental results.…”
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Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid

“…This study evaluates the performance of artificial neural network (ANN) algorithms for FSM using machine learning classification. Traditional flood prediction models face limitations due to data complexity and computational constraints. …”
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In Silico strategies for drug discovery: optimizing natural compounds from foods for therapeutic applications by Romo-Hernández Aarón, Cortazar-Moya Sheila, González-Pérez Julio Emmanuel, Jiménez-González Oscar, López-Malo Aurelio, Morales-Camacho Jocksan Ismael

“…The review focuses on how in silico-based tools, such as machine learning, computer-based mathematical modeling, homology prediction, docking, molecular dynamics, and simulated molecular evolution events, are used to optimize natural compound testing and design. …”
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Sustainable supply chain: An optimization and resource efficiency in additive manufacturing for automotive spare part by Divya Chauhan, Anubhav Pratap Singh, Anand Chauhan, Ritu Arora

“…The optimized model also reduces production cycle time, enhancing sustainability by waste reduction. …”
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Experimental analysis and gene expression programming optimization of sustainable concrete containing mineral fillers by Ayesha Rauf, Usama Asif, Kennedy Onyelowe, Muhammad Faisal Javed, Hisham Alabduljabbar

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